{"instruction": "You are an expert in event extraction. Please extract events from the input that conform to the schema definition. Return an empty list for events that do not exist, and return NAN for arguments that do not exist. If an argument has multiple values, please return a list. Respond in the format of a JSON string.", "schema": [{"event_type": "data breach", "trigger": true, "arguments": ["place", "attack pattern", "number of data", "number of victim", "damage amount", "time", "tool", "attacker", "purpose"]}, {"event_type": "ransom", "trigger": true, "arguments": ["price", "time", "payment method", "attacker"]}, {"event_type": "phishing", "trigger": true, "arguments": ["trusted entity", "attacker", "victim", "tool", "attack pattern", "place", "purpose", "time", "damage amount"]}, {"event_type": "patch vulnerability", "trigger": true, "arguments": ["issues addressed", "releaser", "supported platform", "time", "patch number", "vulnerable system", "vulnerable system version"]}, {"event_type": "discover vulnerability", "trigger": true, "arguments": ["vulnerability", "discoverer", "vulnerable system version", "time", "supported platform", "common vulnerabilities and exposures", "capabilities", "vulnerable system"]}], "input": "Often , recipients are fooled into believing the phishing communication is from someone they trust ."}
{"data breach": [], "ransom": [], "phishing": [{"trigger": "are fooled", "arguments": {"trusted entity": "someone they trust", "attacker": "NAN", "victim": "recipients", "tool": "NAN", "attack pattern": "NAN", "place": "NAN", "purpose": "NAN", "time": "NAN", "damage amount": "NAN"}}], "patch vulnerability": [], "discover vulnerability": []}